ICSID’s Reinforcement?: UNASUR and the Rise of a Hybrid Regime for International Investment Arbitration
Bibliographic record
Abstract
The legitimacy and effectiveness of the International Centre for Settlement of Investment Disputes (“ICSID”) is a matter of spirited debate. Opponents argue that ICSID’s ideological and procedural bias impedes fairness, its complexity and cost restrict access to justice, and its lack of an appeal process exacerbates uncertainty and unpredictability. Dissatisfaction with and ideological critique of ICSID, especially on the part of Latin American states, culminated in 2009 when Ecuador proposed the creation of a regional arbitration centre as part of the Union of South American Nations (“UNASUR”). This article surveys the myriad criticisms launched against ICSID and assesses the likelihood and desirability of the UNASUR Arbitration Centre as an alternative or supplement to ICSID. The article concludes that reforms to ICSID can address most of the problems identified by critics but that the UNASUR Arbitration Centre will continue to gain momentum. The result will be a hybrid international investment law regime, at least in the short- to medium-term. This hybrid regime will be functional, serve an important purpose for Latin American countries, and advance the goals of investment liberalization.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.018 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".